Abstract: A method of determining a location for placement of a package in an imaging controller includes: obtaining depth data of a package space; detecting an occluded portion of the depth data representing an area of the package space obstructed by an occlusion; retrieving stored unobstructed depth data representing the area of the package space in the absence of the occlusion; replacing the occluded portion with the unobstructed depth data to generate patched depth data; obtaining, based on the patched depth data, a location within the package space for placement of a package; and presenting an indication of the location.

Abstract: A method and apparatus for receiving a depth frame from a depth sensor oriented towards an open end of a shipping container, the depth frame comprising a plurality of grid elements that each have a respective depth value, identifying one or more occlusions in the depth frame, correcting the one or more occlusions in the depth frame using one or more temporally proximate depth frames, and outputting the corrected depth frame for fullness estimation.

Abstract: A method of determining a location for placement of a package in an imaging controller includes: obtaining depth data of a package space; detecting an occluded portion of the depth data representing an area of the package space obstructed by an occlusion; retrieving stored unobstructed depth data representing the area of the package space in the absence of the occlusion; replacing the occluded portion with the unobstructed depth data to generate patched depth data; obtaining, based on the patched depth data, a location within the package space for placement of a package; and presenting an indication of the location.

Abstract: A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Abstract: Dimensions of an object associated with an electro-optically readable code are estimated by aiming a handheld device at a scene containing the object supported on a base surface. A scanner on the device scans the scene over a field of view to obtain a position of a reference point of the code associated with the object, and reads the code. A dimensioning sensor on the device captures a three-dimensional (3D) point cloud of data points of the scene in automatic response to the reading of the code. A controller clusters the point cloud into data clusters, locates the reference point of the code in one of the data clusters, extracts from the point cloud the data points of the one data cluster belonging to the object, and processes the extracted data points belonging to the object to estimate the dimensions of the object.

Abstract: A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Abstract: A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Abstract: Dimensions of an object associated with an electro-optically readable code are estimated by aiming a handheld device at a scene containing the object supported on a base surface. A scanner on the device scans the scene over a field of view to obtain a position of a reference point of the code associated with the object, and reads the code. A dimensioning sensor on the device captures a three-dimensional (3D) point cloud of data points of the scene in automatic response to the reading of the code. A controller clusters the point cloud into data clusters, locates the reference point of the code in one of the data clusters, extracts from the point cloud the data points of the one data cluster belonging to the object, and processes the extracted data points belonging to the object to estimate the dimensions of the object.

Abstract: A method and apparatus for receiving a depth frame from a depth sensor oriented towards an open end of a shipping container, the depth frame comprising a plurality of grid elements that each have a respective depth value, identifying one or more occlusions in the depth frame, correcting the one or more occlusions in the depth frame using one or more temporally proximate depth frames, and outputting the corrected depth frame for fullness estimation.

Abstract: A method and apparatus for (a) receiving a three-dimensional (3D) point cloud from a depth sensor that is oriented towards an open end of a shipping container, the point cloud comprising a plurality of points that each have a respective depth value, (b) segmenting the received 3D point cloud among a plurality of grid elements, (c) calculating a respective loaded-container-portion grid-element volume for each grid element, (d) calculating a loaded-container-portion volume of the shipping container by aggregating the calculated respective loaded-container-portion grid-element volumes, (e) calculating an estimated fullness of the shipping container based on the loaded-container-portion volume and a capacity of the shipping container; and (f) outputting the calculated estimated fullness of the shipping container.

Abstract: A non-parametric method of, and system for, dimensioning an object of arbitrary shape, captures a three-dimensional (3D) point cloud of data points over a field of view containing the object and a base surface on which the object is positioned, detects a base plane indicative of the base surface from the point cloud, extracts the data points of the object from the point cloud, processes the extracted data points of the object to obtain a convex hull, and fits a bounding box of minimum volume to enclose the convex hull. The bounding box has a pair of mutually orthogonal planar faces, and the fitting is performed by orienting one of the faces to be generally perpendicular to the base plane, and by simultaneously orienting the other of the faces to be generally parallel to the base plane.

Abstract: Dimensions of an object associated with an electro-optically readable code are estimated by aiming a handheld device at a scene containing the object supported on a base surface. A scanner on the device scans the scene over a field of view to obtain a position of a reference point of the code associated with the object, and reads the code. A dimensioning sensor on the device captures a three-dimensional (3D) point cloud of data points of the scene in automatic response to the reading of the code. A controller clusters the point cloud into data clusters, locates the reference point of the code in one of the data clusters, extracts from the point cloud the data points of the one data cluster belonging to the object, and processes the extracted data points belonging to the object to estimate the dimensions of the object.

Abstract: Dimensions of an object associated with an electro-optically readable code are estimated by aiming a handheld device at a scene containing the object supported on a base surface. A scanner on the device scans the scene over a field of view to obtain a position of a reference point of the code associated with the object, and reads the code. A dimensioning sensor on the device captures a three-dimensional (3D) point cloud of data points of the scene in automatic response to the reading of the code. A controller clusters the point cloud into data clusters, locates the reference point of the code in one of the data clusters, extracts from the point cloud the data points of the one data cluster belonging to the object, and processes the extracted data points belonging to the object to estimate the dimensions of the object.

Abstract: A non-parametric method of, and system for, dimensioning an object of arbitrary shape, captures a three-dimensional (3D) point cloud of data points over a field of view containing the object and a base surface on which the object is positioned, detects a base plane indicative of the base surface from the point cloud, extracts the data points of the object from the point cloud, processes the extracted data points of the object to obtain a convex hull, and fits a bounding box of minimum volume to enclose the convex hull. The bounding box has a pair of mutually orthogonal planar faces, and the fitting is performed by orienting one of the faces to be generally perpendicular to the base plane, and by simultaneously orienting the other of the faces to be generally parallel to the base plane.

Abstract: An embodiment takes the form of a method carried out by a package-loading system. The system includes a processor and data storage containing instructions executable by the processor for carrying out the method. The method includes identifying a current package to be loaded by a user into a cargo container, and determining a target position in the cargo container for placement by the user of the identified current package. The method further includes providing for the user a visual indication of the determined target position.

Abstract: A technique for real-time trailer utilization measurement includes a three-dimensional depth monitor operable to monitor loading of a trailer and a processor operable to determine trailer utilization in real-time during loading of the trailer using image information from the monitor. A graphical user interface can receive utilization information from the processor and display a visual representation of real-time loading of the trailer. Utilization is a ratio of cumulative package volume to currently loaded volume of the trailer, wherein the cumulative package volume is determined from dimensional scans of packages to be loaded in the trailer and the currently loaded volume is determined by the monitor.

Abstract: A technique for trailer loading assessment includes imaging loading of a trailer using a monitor. A next step includes detecting loading incidents related to package stacking quality during loading of the trailer using image information from the monitor. A next step includes bookmarking detected loading incidents. A next step includes scoring loading incidents. A next step includes displaying, on a graphical user interface, a visual representation of the loading incidents. The monitor can be an infrared three-dimensional depth camera operable to measure distance to a stacked wall of loaded packages, and a video camera operable to provide an optical image to detect loading incidents.

Abstract: Disclosed is a “bundle” of event-related multi-media content items provided to a customer of the event. The customer navigates through the bundle, tracks down selections of interest to himself, and “consumes” them. In some embodiments, the multi-media content items include recorded video clips, interviews, and other background information. Other content items can be live video feeds of the event taken from various viewpoints. Advertising for merchandise related to the event can be included. Some of the multi-media content items are designed to enhance the customer's experience of the event or to build loyalty. The media bundle is updated during the course of the event, removing items no longer of interest and adding new ones to keep the customer engaged. When the event is over, the media bundle can continue to operate to provide event recaps, post-event interviews, schedules for future events, and opportunities to purchase tickets for those future events.

Abstract: A method, apparatus, and electronic device for processing video data are disclosed. A video capture mechanism 202 may capture the video data. A key frame extractor 204 may extract a key frame from the video data automatically based on a set of criteria. A video encoder 206 may encode the video data with a key frame identifier.

Abstract: A method for head pose estimation may include receiving block motion vectors for a frame of video from a block motion estimator, selecting at least one block for analysis, determining an average motion vector for the at least one selected block, combining the average motion vectors over time (all past frames of video) to determine an accumulated average motion vector, estimating the orientation of a user's head in the video frame based on the accumulated average motion vector, and outputting at least one parameter indicative of the estimated orientation.